• DocumentCode
    3282157
  • Title

    Research on public opinion based on Big Data

  • Author

    Songtao Shang ; Minyong Shi ; Wenqian Shang ; Zhiguo Hong

  • Author_Institution
    Sch. of Comput. Sci., Commun. Univ. of China, Beijing, China
  • fYear
    2015
  • fDate
    June 28 2015-July 1 2015
  • Firstpage
    559
  • Lastpage
    562
  • Abstract
    Public opinion is the people´s response for social phenomena, issues, hot topics, attitudes, emotions, and so on. It reflects the focus problems of the current time of the society. By analyzing the public opinion, we can infer what will happen in the next time, and give better decision support for governments and businesses. Big Data technology is becoming a powerful data analyzing tools for massive data in recent years. Hadoop is an open source massive data processing platform based on Big Data. Mahout is a data mining algorithms´ set based on Hadoop, which is designed for processing large-scale and complex data. In most instances, the public opinion information contains many text messages. For many traditional text mining algorithms, it is almost impossible to handle high dimensional data concerns large-volume and complex data sets. Hence, this paper uses Mahout text mining algorithms to process public opinion information.
  • Keywords
    Big Data; Internet; data analysis; data mining; text analysis; Big Data technology; Hadoop; Mahout text mining algorithms; data analyzing tools; data mining algorithm; open source massive data processing platform; public opinion; Algorithm design and analysis; Big data; Classification algorithms; Clustering algorithms; Data mining; Internet; Machine learning algorithms; Big Data; Hadoop; Mahout; data mining; public opinion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Science (ICIS), 2015 IEEE/ACIS 14th International Conference on
  • Conference_Location
    Las Vegas, NV
  • Type

    conf

  • DOI
    10.1109/ICIS.2015.7166655
  • Filename
    7166655